In [1]:
# load required modules
import scanpy as sc
import besca as bc
import pandas as pd
import numpy as np
import os
import pkg_resources
#import numpy as np
#from matplotlib import pyplot
#import sys
#setup document
sc.settings.verbosity = 3 # verbosity: errors (0), warnings (1), info (2), hints (3)
sc.settings.set_figure_params(dpi=80) # low dpi (dots per inch) yields small inline figures
sc.logging.print_header()
scanpy==1.6.0 anndata==0.7.4 umap==0.3.10 numpy==1.17.4 scipy==1.5.1 pandas==1.0.5 scikit-learn==0.22 statsmodels==0.11.1 python-igraph==0.8.0 leidenalg==0.7.0
In [2]:
# define filepath (this is the folder that contains "raw" and "analyzed")
root_path = os.getcwd()
# input: results from standard workflow
analysis_name = 'standard_workflow_besca'
results_folder = os.path.join(root_path, 'analyzed', analysis_name)
input_data = os.path.join(results_folder, 'standard_workflow_besca.h5ad') # specify a .h5ad file for storing the results
# define output directories
outdir_data = results_folder
outdir_figures = os.path.join(results_folder, 'figures')
outdir_results = os.path.join(results_folder, 'results')
sc.settings.figdir = os.path.join(outdir_figures)
os.makedirs(outdir_data, exist_ok=True)
os.makedirs(outdir_figures, exist_ok=True)
os.makedirs(outdir_results, exist_ok=True)
In [3]:
#reload our data from previously written out AnnData object
adata = sc.read(input_data)
#adata = bc.datasets.Haber2017_processed()
In [4]:
adata = bc.st.additional_labeling(adata, 'leiden', 'leiden', 'Leiden clustering from standard workflow.', 'Klas Hatje', outdir_data)
ranking genes
finished: added to `.uns['rank_genes_groups']`
'names', sorted np.recarray to be indexed by group ids
'scores', sorted np.recarray to be indexed by group ids
'logfoldchanges', sorted np.recarray to be indexed by group ids
'pvals', sorted np.recarray to be indexed by group ids
'pvals_adj', sorted np.recarray to be indexed by group ids (0:00:15)
rank genes per label calculated using method wilcoxon.
mapping of cells to leiden exported successfully to cell2labels.tsv
average.gct exported successfully to file
fract_pos.gct exported successfully to file
labelinfo.tsv successfully written out
/pstore/data/bi/reference/scseq/GSE92332_mouse_small_intestine/analyzed/standard_workflow_besca/labelings/leiden/WilxRank.gct written out
/pstore/data/bi/reference/scseq/GSE92332_mouse_small_intestine/analyzed/standard_workflow_besca/labelings/leiden/WilxRank.pvalues.gct written out
/pstore/data/bi/reference/scseq/GSE92332_mouse_small_intestine/analyzed/standard_workflow_besca/labelings/leiden/WilxRank.logFC.gct written out
In [5]:
adata
Out[5]:
AnnData object with n_obs × n_vars = 10896 × 1233
obs: 'CELL', 'CONDITION', 'sample_type', 'donor', 'region', 'sample', 'percent_mito', 'n_counts', 'n_genes', 'batch', 'leiden'
var: 'ENSEMBL', 'SYMBOL', 'n_cells', 'total_counts', 'frac_reads', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std'
uns: 'hvg', 'leiden', 'leiden_colors', 'neighbors', 'pca', 'rank_genes_groups', 'region_colors', 'umap'
obsm: 'X_pca', 'X_umap'
varm: 'PCs'
obsp: 'connectivities', 'distances'
In [6]:
adata.obs.head()
Out[6]:
| CELL | CONDITION | sample_type | donor | region | sample | percent_mito | n_counts | n_genes | batch | leiden | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| haber_intestine_donor_M1_Duo.AAACATACAGCGGA | haber_intestine_donor_M1_Duo.AAACATACAGCGGA | healthy | mouse_small_intestine_epithelial | M1 | Duo | Duo_M1 | 0.001410 | 12768.0 | 1227 | Duo | 22 |
| haber_intestine_donor_M1_Duo.AAACATACCTTACT | haber_intestine_donor_M1_Duo.AAACATACCTTACT | healthy | mouse_small_intestine_epithelial | M1 | Duo | Duo_M1 | 0.010779 | 6583.0 | 2156 | Duo | 3 |
| haber_intestine_donor_M1_Duo.AAACCGTGCAGTCA | haber_intestine_donor_M1_Duo.AAACCGTGCAGTCA | healthy | mouse_small_intestine_epithelial | M1 | Duo | Duo_M1 | 0.022508 | 2799.0 | 1362 | Duo | 1 |
| haber_intestine_donor_M1_Duo.AAACGCTGCAGTCA | haber_intestine_donor_M1_Duo.AAACGCTGCAGTCA | healthy | mouse_small_intestine_epithelial | M1 | Duo | Duo_M1 | 0.015041 | 6048.0 | 2287 | Duo | 9 |
| haber_intestine_donor_M1_Duo.AAACGCTGCGTGAT | haber_intestine_donor_M1_Duo.AAACGCTGCGTGAT | healthy | mouse_small_intestine_epithelial | M1 | Duo | Duo_M1 | 0.023022 | 2780.0 | 1320 | Duo | 17 |
In [ ]:
In [7]:
%matplotlib inline
sc.settings.set_figure_params(dpi=90)
In [8]:
sc.pl.umap(adata, color=['leiden', 'region'], legend_loc='on data', legend_fontsize=9)
In [9]:
sc.tl.tsne(adata)
sc.pl.tsne(adata, color=['leiden', 'region'], legend_loc='on data', legend_fontsize=9)
computing tSNE
using 'X_pca' with n_pcs = 50
using the 'MulticoreTSNE' package by Ulyanov (2017)
finished: added
'X_tsne', tSNE coordinates (adata.obsm) (0:01:13)
In [10]:
#sc.pl.umap(adata, color=['leiden', 'celltype'], legend_loc='on data', legend_fontsize=6)
In [11]:
#sc.pl.umap(adata, color=['Subtype'], legend_fontsize=9)
In [ ]:
In [12]:
### Perform DE cells of each Subtype vs. all other cells
DEgenes=bc.tl.dge.get_de(adata,'leiden',demethod='wilcoxon',topnr=5000, logfc=1,padj=0.05)
ranking genes
finished: added to `.uns['rank_genes_groups']`
'names', sorted np.recarray to be indexed by group ids
'scores', sorted np.recarray to be indexed by group ids
'logfoldchanges', sorted np.recarray to be indexed by group ids
'pvals', sorted np.recarray to be indexed by group ids
'pvals_adj', sorted np.recarray to be indexed by group ids (0:00:15)
In [13]:
### Select only top genes (in order of p-val) and plot expression per cell type
tops=list(DEgenes['12']['Name'][0:15])+list(DEgenes['13']['Name'][0:15])
#tops=list(DEgenes['Naive T cells']['Name'][0:30])
sc.pl.dotplot(adata, var_names=tops,groupby='leiden')
In [ ]:
In [14]:
#sc.pl.dotplot(adata, var_names=['SELL', 'CCR7', 'ID3', 'TCF7', 'LEF1', 'NELL2', 'PASK', 'FLT3LG', 'CAMK4', 'MAL'],groupby='Subtype')
In [ ]:
In [15]:
# Load GMT file and calculate signature scores
gmt_file_IMM=pkg_resources.resource_filename('besca', 'datasets/genesets/HumanCD45p_scseqCMs6.gmt')
gmt_file_anno=pkg_resources.resource_filename('besca', 'datasets/genesets/CellNames_scseqCMs6_sigs.gmt')
gmt_file_crypt=pkg_resources.resource_filename('besca', 'datasets/genesets/CryptScoreParikh2019.gmt')
mousehuman_file = pkg_resources.resource_filename('besca', 'datasets/homologs/MGItoHGNC.csv')
mousehuman=pd.read_csv(mousehuman_file,sep='\t',header='infer', encoding="unicode_escape")
mousehuman.index=mousehuman['MGI']
conversion=pd.Series(data=mousehuman['HGNC'], index=mousehuman.index)
adata_IMM_scores = adata.copy()
adata_anno_scores = adata.copy()
adata_crypt_scores = adata.copy()
bc.tl.sig.combined_signature_score(adata_IMM_scores, gmt_file_IMM, conversion=conversion)
bc.tl.sig.combined_signature_score(adata_anno_scores, gmt_file_anno, conversion=conversion)
bc.tl.sig.combined_signature_score(adata_crypt_scores, gmt_file_crypt, conversion=conversion)
computing score 'score_HumanCD45p_scseqCMs6_ActB_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Fcrl5', 'Ccr7', 'Cd40', 'Batf']
finished: added
'score_HumanCD45p_scseqCMs6_ActB_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Activation_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd69', 'Ccl5', 'Tnfrsf9']
finished: added
'score_HumanCD45p_scseqCMs6_Activation_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Basophil_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr3', 'Cd69', 'Tlr4']
finished: added
'score_HumanCD45p_scseqCMs6_Basophil_scanpyUP', score of gene set (adata.obs).
300 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Bcells_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd19', 'Ms4a1', 'Cd79a']
finished: added
'score_HumanCD45p_scseqCMs6_Bcells_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_CCG1S_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_CCG1S_scanpyUP', score of gene set (adata.obs).
645 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_CCG2M_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_CCG2M_scanpyUP', score of gene set (adata.obs).
550 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Cafs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Thy1', 'Dcn', 'Col1a1', 'Col1a2', 'Col6a1', 'Col6a2', 'Col6a3', 'Cxcl14', 'Lum', 'Col3a1', 'Dpt', 'Islr', 'Cd248', 'Mxra8']
finished: added
'score_HumanCD45p_scseqCMs6_Cafs_scanpyUP', score of gene set (adata.obs).
49 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Cellcycle_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_Cellcycle_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Checkpoint_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tigit', 'Cd274', 'Lag3', 'Pdcd1', 'Havcr2']
finished: added
'score_HumanCD45p_scseqCMs6_Checkpoint_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Cyto_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ifng', 'Il4', 'Il6', 'Il10', 'Il13', 'Il16', 'Il21', 'Il22', 'Il1b', 'Gzmb', 'Prf1', 'Cxcl9', 'Cxcl10', 'Cxcl11', 'Cxcl12', 'Ccl2', 'Ccl3', 'Ccl5', 'Ccl7', 'Ccl11', 'Ccl17', 'NaN', 'Ccl22', 'Ccl24', 'Ccl8']
finished: added
'score_HumanCD45p_scseqCMs6_Cyto_scanpyUP', score of gene set (adata.obs).
350 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Cytotox_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Nkg7', 'Gzmb', 'Gzmk', 'Gzma', 'Crtam', 'Cst7']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_DCR_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tlr8']
finished: added
'score_HumanCD45p_scseqCMs6_DCR_scanpyUP', score of gene set (adata.obs).
349 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_DCrec_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tlr8']
finished: added
'score_HumanCD45p_scseqCMs6_DCrec_scanpyUP', score of gene set (adata.obs).
349 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_DCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr2', 'Ccr7', 'Rnase6', 'Clec9a', 'Btla', 'Tlr7', 'Klrd1', 'Ccr7']
finished: added
'score_HumanCD45p_scseqCMs6_DCs_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Eff_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr3', 'Tbx21', 'Eomes', 'Prf1', 'Ccr10', 'Aqp3', 'Dusp2']
finished: added
'score_HumanCD45p_scseqCMs6_Eff_scanpyUP', score of gene set (adata.obs).
49 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Endo_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd34', 'Cdh5', 'Eng', 'Flt4', 'Itgb3', 'Kdr', 'Mcam', 'Pecam1', 'Procr', 'Sele', 'Tek', 'Vcam1']
finished: added
'score_HumanCD45p_scseqCMs6_Endo_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Endot_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd34', 'Cdh5', 'Flt4', 'Itgb3', 'Kdr', 'Mcam', 'Pecam1', 'Procr', 'Sele', 'Tek', 'Vcam1']
finished: added
'score_HumanCD45p_scseqCMs6_Endot_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Endothelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pecam1', 'Cdh5', 'Cldn5', 'Plvap', 'Mmrn1', 'Kdr', 'Tie1', 'Erg', 'Fabp4']
finished: added
'score_HumanCD45p_scseqCMs6_Endothelial_scanpyUP', score of gene set (adata.obs).
198 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Eosinophil_scanpyUP'
WARNING: genes are not in var_names and ignored: ['C3ar1', 'C5ar1', 'Ccr1l1', 'Ccr3', 'Cd244a', 'Cd52', 'Cd53', 'Cxcr3', 'Fcer2a', 'Il9r', 'Itga4', 'Lair1', 'Ptgdr2', 'Gm5849', 'Siglece']
finished: added
'score_HumanCD45p_scseqCMs6_Eosinophil_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Epith_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_Epith_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_ExhB_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Nr4a3', 'Egr3', 'Nr4a1', 'Egr2']
finished: added
'score_HumanCD45p_scseqCMs6_ExhB_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Granulo_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Csf3r', 'Itgax', 'Gm5849', 'Hcar2', 'Clec4d', 'S100a8', 'Retn']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_HLA_scanpyUP'
WARNING: genes are not in var_names and ignored: ['H2-Eb2']
finished: added
'score_HumanCD45p_scseqCMs6_HLA_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_HLAP_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_HLAP_scanpyUP', score of gene set (adata.obs).
498 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_HLAS_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_HLAS_scanpyUP', score of gene set (adata.obs).
349 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Ifi_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Mx2', 'Ifitm7']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Ifng_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcl9', 'Cxcl10', 'Ido1', 'Ifng']
finished: added
'score_HumanCD45p_scseqCMs6_Ifng_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Macrophage_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd86', 'Ccr1l1', 'Ccr5', 'Adgre1', 'C1qa', 'C1qb', 'Gm15922', 'Csf1r', 'Msr1', 'Gpr34']
finished: added
'score_HumanCD45p_scseqCMs6_Macrophage_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Mast_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_Mast_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Megakaryocytes_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr4', 'Gp1ba', 'Itga2b', 'Itgb3', 'Pecam1', 'Selp']
finished: added
'score_HumanCD45p_scseqCMs6_Megakaryocytes_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_MelMelan_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gm21983', 'Tyr', 'Slc45a2', 'Cdh19', 'Capn3', 'Gpm6b', 'S100b', 'Pax3', 'Mlana']
finished: added
'score_HumanCD45p_scseqCMs6_MelMelan_scanpyUP', score of gene set (adata.obs).
300 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_MelMesen_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Rgs5', 'Bgn', 'Tnc', 'Igfbp6', 'Gfra2']
finished: added
'score_HumanCD45p_scseqCMs6_MelMesen_scanpyUP', score of gene set (adata.obs).
499 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_MemB_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tnfrsf13b', 'Igha', 'Cd27', 'Cxcr3']
finished: added
'score_HumanCD45p_scseqCMs6_MemB_scanpyUP', score of gene set (adata.obs).
250 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Memory_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Il7r', 'Cxcr4', 'Gpr183', 'Cd84']
finished: added
'score_HumanCD45p_scseqCMs6_Memory_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Mo14_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_Mo14_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Mo16_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Fcgr4']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_MoMa_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Fcgr2b', 'Fcgr4', 'Ccr1l1']
finished: added
'score_HumanCD45p_scseqCMs6_MoMa_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Monocytes_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Fcgr2b', 'Fcgr4', 'Gpr34', 'Ms4a7', 'Fcgr1', 'Msr1']
finished: added
'score_HumanCD45p_scseqCMs6_Monocytes_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Myelo_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tyrobp', 'Ccr2', 'Cd34', 'Fcgr1']
finished: added
'score_HumanCD45p_scseqCMs6_Myelo_scanpyUP', score of gene set (adata.obs).
199 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_MyeloSubtype_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Siglech', 'Gm5849', 'S100a8', 'Cd80']
finished: added
'score_HumanCD45p_scseqCMs6_MyeloSubtype_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_NKT_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tyrobp', 'Fcer1g', 'Clic3']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_NKcells_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sh2d1b2', 'Il2rb', 'Trdc', 'Xcl1', 'Igfbp7', 'Ncr1', 'Il18rap']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_NKcyt_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd160', 'Spon2', 'Fcgr4', 'Cd247', 'Ccl4']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_NKnai_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Xcl1', 'Sell', 'Ccr7', 'Fut7']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Naive_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sell', 'Ccr7', 'Lef1']
finished: added
'score_HumanCD45p_scseqCMs6_Naive_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_NaiveB_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ighm', 'Tcl1', 'Sell', 'Fcer2a', 'Satb1', 'Btla']
finished: added
'score_HumanCD45p_scseqCMs6_NaiveB_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Neutrophil_scanpyUP'
WARNING: genes are not in var_names and ignored: ['C5ar1', 'Siglech', 'Csf3r', 'Cxcr1', 'Cxcr2', 'Fcgr1', 'Itgax']
finished: added
'score_HumanCD45p_scseqCMs6_Neutrophil_scanpyUP', score of gene set (adata.obs).
249 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_NonEff_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd27', 'Cd28']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_OMyelo_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd34']
finished: added
'score_HumanCD45p_scseqCMs6_OMyelo_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Others_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tyrobp']
finished: added
'score_HumanCD45p_scseqCMs6_Others_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Plasma_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd79a', 'Igf1', 'Itga8']
finished: added
'score_HumanCD45p_scseqCMs6_Plasma_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Pyro_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_Pyro_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Stemmess_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cdh2', 'Loxl2']
finished: added
'score_HumanCD45p_scseqCMs6_Stemmess_scanpyUP', score of gene set (adata.obs).
647 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_StemmessS_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_StemmessS_scanpyUP', score of gene set (adata.obs).
199 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Stromal_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Icam2', 'Itga4', 'Madcam1', 'Mmp1a', 'Mmp2', 'Mmp9', 'Pdgfra', 'Pecam1', 'Thy1', 'Timp1', 'Tlr4', 'Vcam1']
finished: added
'score_HumanCD45p_scseqCMs6_Stromal_scanpyUP', score of gene set (adata.obs).
399 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_T4CM_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gpr183', 'Aqp3', 'Fut7', 'Cd84', 'Gpr171']
finished: added
'score_HumanCD45p_scseqCMs6_T4CM_scanpyUP', score of gene set (adata.obs).
300 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TAM_scanpyUP'
WARNING: genes are not in var_names and ignored: ['C1qa', 'C1qb', 'Gpr34', 'C3', 'Cxcl12', 'Siglec1', 'Cd209c', 'F13a1', 'Msr1']
finished: added
'score_HumanCD45p_scseqCMs6_TAM_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TAMCx_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcl10', 'Cxcl11', 'Cxcl9']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_TEM_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tigit', 'Gzmk', 'Cd84', 'Cd27', 'Dusp2', 'Gpr171']
finished: added
'score_HumanCD45p_scseqCMs6_TEM_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TMO_scanpyUP'
WARNING: genes are not in var_names and ignored: ['S100a8', 'Gm5849', 'Vcan', 'Cd300e', 'Il1b']
finished: added
'score_HumanCD45p_scseqCMs6_TMO_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TMid_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Marco', 'Clec5a']
finished: added
'score_HumanCD45p_scseqCMs6_TMid_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TNK_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd2', 'Cd7', 'Lat', 'Cd6', 'Cd96', 'Lat', 'Cd247']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_TStem_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr5', 'Cxcr3', 'Pdcd1', 'Slamf6', 'Il18r1', 'Il7r']
finished: added
'score_HumanCD45p_scseqCMs6_TStem_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TStemhi_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr5', 'Cxcr3', 'Pdcd1', 'Slamf6', 'Il18r1', 'Il7r']
finished: added
'score_HumanCD45p_scseqCMs6_TStemhi_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TSteml_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd27', 'Cd28', 'Icos', 'Il2ra']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_TStemlo_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd27', 'Cd28', 'Icos', 'Il2ra']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_TTh1_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr1l1', 'Ccr5', 'Cd4', 'Csf2', 'Cxcr3', 'Havcr2', 'Ifna9', 'Klrd1', 'Tnfsf11']
finished: added
'score_HumanCD45p_scseqCMs6_TTh1_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TTh17_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr4', 'Ccr6', 'Cd4', 'Il17a', 'Il1r1', 'Il21', 'Il22', 'Klrb1f']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_TTh2_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr3', 'Ccr4', 'Ccr7', 'Ccr8', 'Cd4', 'Csf2', 'Gata3', 'Timd2', 'Icos', 'Icos', 'Il10', 'Il13', 'Il1r1', 'Il4', 'Il5', 'Il6', 'Ptgdr2']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Tcd4_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd4', 'Gpr183']
finished: added
'score_HumanCD45p_scseqCMs6_Tcd4_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Tcd8_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd8a', 'Cd8b1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Tcells_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd3e', 'Cd3d', 'Cd3g', 'Trat1']
finished: added
'score_HumanCD45p_scseqCMs6_Tcells_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Tcgd_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcrg-C1', 'Trdc']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Tcytox_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcrg-C1', 'Klrd1', 'Fcgr4', 'Gzmb', 'Prf1', 'Spon2', 'Clic3']
finished: added
'score_HumanCD45p_scseqCMs6_Tcytox_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Teff_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd8a', 'Gzma', 'Gzmb', 'Ifng', 'Eomes', 'Cxcl9', 'Cxcl10', 'Tbx21', 'Cd274', 'Pdcd1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_Tfh_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Bcl6', 'Cd40lg', 'Cd84', 'Cxcr5', 'Icos', 'Pdcd1', 'Cd4']
finished: added
'score_HumanCD45p_scseqCMs6_Tfh_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_TilCM_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr6', 'Slc4a10', 'Il7r', 'Il18rap', 'Zbtb16', 'Cebpd', 'Slc4a10', 'Ccr2', 'Adam12', 'Klrb1f', 'Gzmk']
finished: added
'score_HumanCD45p_scseqCMs6_TilCM_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Tpexh_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Icos', 'Tnfsf14', 'Sell', 'Il7r', 'Lef1', 'Satb1', 'Bcl6', 'Cxcr5', 'Ccr7', 'Xcl1', 'Cxcl10']
finished: added
'score_HumanCD45p_scseqCMs6_Tpexh_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Treg_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Foxp3', 'Il2ra', 'Lrrc32']
finished: added
'score_HumanCD45p_scseqCMs6_Treg_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Ttexh_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pdcd1', 'Havcr2', 'Lag3', 'Cd244a', 'Entpd1', 'Cd101', 'Tnfrsf9', 'Il2rb', 'Ifng', 'Il10', 'Gzma', 'Gzmb', 'Prf1', 'Prdm1', 'Runx3', 'Tbx21', 'Cxcr1', 'Ccl5', 'Ccl4', 'Ccl3', 'Csf1']
finished: added
'score_HumanCD45p_scseqCMs6_Ttexh_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_Ubi_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gm17087']
finished: added
'score_HumanCD45p_scseqCMs6_Ubi_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_UnivExh_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Nr4a3', 'Egr3', 'Nr4a1', 'Egr2']
finished: added
'score_HumanCD45p_scseqCMs6_UnivExh_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_UnivMem_scanpyUP'
finished: added
'score_HumanCD45p_scseqCMs6_UnivMem_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_UnivNaive_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sell']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_HumanCD45p_scseqCMs6_aDCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccr7', 'Ccl22', 'Ccl17', 'Fscn1', 'NaN', 'Nudt17']
finished: added
'score_HumanCD45p_scseqCMs6_aDCs_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_allSteml_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pdcd1', 'Cd28', 'Cxcr5', 'Il2ra', 'Havcr2', 'Slamf6', 'Il2rb', 'Gzmb', 'S1pr1', 'Cxcr3', 'Ifng', 'Il18r1', 'Cd244a', 'Il10', 'Entpd1']
finished: added
'score_HumanCD45p_scseqCMs6_allSteml_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_cDC1_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec9a', 'Batf3', 'Xcr1', 'Wdfy4', 'Clnk', 'Asb2']
finished: added
'score_HumanCD45p_scseqCMs6_cDC1_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_cDC2_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec10a', 'Fcer1a', 'Pkib']
finished: added
'score_HumanCD45p_scseqCMs6_cDC2_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_cDCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec9a', 'Btla', 'Clec10a', 'Pkib', 'Xcr1']
finished: added
'score_HumanCD45p_scseqCMs6_cDCs_scanpyUP', score of gene set (adata.obs).
300 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_epDCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Klrd1']
finished: added
'score_HumanCD45p_scseqCMs6_epDCs_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_general_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ptprc', 'Gm17087', 'Bcl6']
finished: added
'score_HumanCD45p_scseqCMs6_general_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_moDC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Lypd2']
finished: added
'score_HumanCD45p_scseqCMs6_moDC_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_pDCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tlr7', 'Lilra6', 'Runx2', 'Irf4', 'Clic3']
finished: added
'score_HumanCD45p_scseqCMs6_pDCs_scanpyUP', score of gene set (adata.obs).
400 total control genes are used. (0:00:00)
computing score 'score_HumanCD45p_scseqCMs6_uDCs_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Klrd1', 'C7']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Bcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd19', 'Ms4a1', 'Tnfrsf13c', 'Cd22']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Fibroblast_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Col6a1', 'Mxra8', 'Acta2', 'Tagln', 'Bgn']
finished: added
'score_Fibroblast_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_Endothelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cdh5', 'Cldn5', 'Kdr', 'Tie1', 'Dnase1l3', 'Akap12', 'Ptprb', 'Stab2']
finished: added
'score_Endothelial_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_Epithelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Klk1b27']
finished: added
'score_Epithelial_scanpyUP', score of gene set (adata.obs).
349 total control genes are used. (0:00:00)
computing score 'score_Granulocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Elane', 'Mpo', 'Prtn3', 'Ctsg', 'Ms4a3', 'Hdc']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_MelMelanoma_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gm21983', 'Tyr', 'Slc45a2', 'Cdh19', 'Capn3', 'Gpm6b', 'S100b', 'Pax3', 'Mlana']
finished: added
'score_MelMelanoma_scanpyUP', score of gene set (adata.obs).
300 total control genes are used. (0:00:00)
computing score 'score_MemBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tnfrsf13b', 'Igha']
finished: added
'score_MemBcell_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Myeloid_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Csf3r', 'Gm5849', 'Lilra6', 'Msr1', 'Marco', 'Mpo']
finished: added
'score_Myeloid_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_NKcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sh2d1b2', 'Ptgdr', 'Il2rb', 'Trdc', 'Xcl1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_NaiBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ighm', 'Cd72', 'Tcl1', 'Fcer2a', 'Btla', 'Fcrl1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Neutrophil_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Elane', 'Mpo', 'Prtn3', 'Ctsg']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Plasma_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd79a', 'Itga8', 'Tnfrsf17', 'Pkhd1l1', 'Jsrp1']
finished: added
'score_Plasma_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_CD4Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd4', 'Trat1']
finished: added
'score_CD4Tcell_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_CD8Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd8a', 'Cd8b1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd3e', 'Cd3d', 'Cd3g', 'Trat1', 'Cd2']
finished: added
'score_Tcell_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_CD8Tcell_IL7Rmax_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr6', 'Slc4a10', 'Il7r', 'Il18rap', 'Zbtb16', 'Cebpd', 'Slc4a10', 'Ccr2', 'Adam12', 'Klrb1f', 'Gzmk']
finished: added
'score_CD8Tcell_IL7Rmax_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_CD4Tcell_IL7Rmax_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr6', 'Slc4a10', 'Il7r', 'Il18rap', 'Zbtb16', 'Cebpd', 'Slc4a10', 'Ccr2', 'Adam12', 'Klrb1f', 'Gzmk']
finished: added
'score_CD4Tcell_IL7Rmax_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_RegTcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Foxp3', 'Il2ra', 'Lrrc32']
finished: added
'score_RegTcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_cDC1_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec9a', 'Xcr1', 'Zfp366', 'Batf3']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_cDC2_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Enho', 'Clec10a', 'Fcer1a']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_cDC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec9a', 'Xcr1', 'Zfp366', 'Batf3', 'Ccl22', 'Ccl17', 'NaN', 'Nudt17', 'Enho', 'Clec10a', 'Axl', 'Gm15922']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_NClassMonocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Fcgr4']
finished: added
'score_NClassMonocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_pDC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Clec4b2', 'Ptcra', 'Lamp5', 'Dntt', 'Ccr9', 'Cox6a2']
finished: added
'score_pDC_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_Hematopoietic_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ptprc', 'Coro1a', 'Cd53', 'Laptm5', 'Cxcr4']
finished: added
'score_Hematopoietic_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_Blymphocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd19', 'Ms4a1', 'Cd79a', 'Itga8', 'Iglc1', 'Pou2af1']
finished: added
'score_Blymphocyte_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_CD56dimNK_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd160', 'Spon2', 'Fcgr4', 'Ccl4', 'S1pr5']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_CD56brightNK_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Xcl1', 'Sell', 'Ccr7', 'Fut7']
finished: added
'score_CD56brightNK_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_NaiCD4Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sell', 'Ccr7', 'Lef1', 'Nell2', 'Camk4', 'Mal']
finished: added
'score_NaiCD4Tcell_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_NaiCD8Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sell', 'Ccr7', 'Lef1', 'Nell2', 'Camk4', 'Mal']
finished: added
'score_NaiCD8Tcell_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_ProlifCD8Tcell_scanpyUP'
finished: added
'score_ProlifCD8Tcell_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ProlifCD4Tcell_scanpyUP'
finished: added
'score_ProlifCD4Tcell_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ProlifBcell_scanpyUP'
finished: added
'score_ProlifBcell_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_CMCD4Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pkia', 'Ap3m2', 'Aqp3']
finished: added
'score_CMCD4Tcell_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_EMCD8Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tigit', 'Gzmk', 'Cd84', 'Cd27', 'Dusp2', 'Gpr171']
finished: added
'score_EMCD8Tcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_EMCD4Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tigit', 'Gzmk', 'Cd84', 'Cd27', 'Dusp2', 'Gpr171']
finished: added
'score_EMCD4Tcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ClassMonocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Vcan']
finished: added
'score_ClassMonocyte_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Macrophage_MARCO_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Marco']
finished: added
'score_Macrophage_MARCO_scanpyUP', score of gene set (adata.obs).
148 total control genes are used. (0:00:00)
computing score 'score_NKTcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd2', 'Cd7', 'Lat', 'Cd6', 'Cd96', 'Lat', 'Cd247']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_gdTcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcrg-C1', 'Trdc', 'Tcrg-C1', 'Klrg1', 'Tcrg-C1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_CytotoxCD4Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcrg-C1', 'Klrd1', 'Fcgr4', 'Gzmb', 'Prf1', 'Spon2', 'Clic3', 'Samd3']
finished: added
'score_CytotoxCD4Tcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_CytotoxCD8Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcrg-C1', 'Klrd1', 'Fcgr4', 'Gzmb', 'Prf1', 'Spon2', 'Clic3', 'Samd3']
finished: added
'score_CytotoxCD8Tcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ExhCD8Tcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pdcd1', 'Havcr2', 'Lag3', 'Cd244a', 'Entpd1', 'Cd101', 'Tnfrsf9', 'Il2rb', 'Ifng', 'Il10', 'Gzma', 'Gzmb', 'Prf1', 'Prdm1', 'Runx3', 'Tbx21', 'Cxcr1', 'Ccl5', 'Ccl4', 'Ccl3', 'Csf1']
finished: added
'score_ExhCD8Tcell_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_cDC_CCR7_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccl22', 'Ccl17', 'NaN', 'Nudt17', 'Ccr7']
finished: added
'score_cDC_CCR7_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Langerhans_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Klrd1']
finished: added
'score_Langerhans_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_Macrophage_MSR1_scanpyUP'
WARNING: genes are not in var_names and ignored: ['C1qa', 'Gpr34', 'C3', 'Cxcl12', 'Siglec1', 'Cd209c', 'F13a1', 'Msr1', 'Fcgr1']
finished: added
'score_Macrophage_MSR1_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_Macrophage_CXCL9_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcl10', 'Cxcl11', 'Cxcl9', 'Fcgr1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Monocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Lypd2', 'Vcan', 'Cd300e', 'Mmp9']
finished: added
'score_Monocyte_scanpyUP', score of gene set (adata.obs).
199 total control genes are used. (0:00:00)
computing score 'score_ExhBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Nr4a3', 'Egr3', 'Nr4a1', 'Egr2']
finished: added
'score_ExhBcell_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_Macrophage_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Msr1', 'Gpr34', 'Cd209c', 'Marco', 'Cxcl10', 'Cxcl11', 'Csf1r', 'Pou2f2']
finished: added
'score_Macrophage_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Hepatocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tat']
finished: added
'score_Hepatocyte_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_Erythrocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ermap', 'Car1']
finished: added
'score_Erythrocyte_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_AlphaPancreatic_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gc', 'Irx2']
finished: added
'score_AlphaPancreatic_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_BetaPancreatic_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ins1', 'Adcyap1', 'Mafa']
finished: added
'score_BetaPancreatic_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_DeltaPancreatic_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Lepr']
finished: added
'score_DeltaPancreatic_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_PPcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ppy', 'Stmn2', 'Fgb', 'Meis1']
finished: added
'score_PPcell_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_PancreaticDuctal_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cldn10', 'Slpi']
finished: added
'score_PancreaticDuctal_scanpyUP', score of gene set (adata.obs).
349 total control genes are used. (0:00:00)
computing score 'score_PancreaticAcinar_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cpa1', 'Ctrb1', 'Ctrc', 'Klk1b27', 'Cel', 'Cela3b']
finished: added
'score_PancreaticAcinar_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_EpsilonPancreatic_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Frzb', 'Sptssb', 'Nnmt']
finished: added
'score_EpsilonPancreatic_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_PancStellate_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Rgs5', 'Notch3', 'Ndufa4l2', 'Ppp1r14a', 'Plac9b']
finished: added
'score_PancStellate_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_Cholangiocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tff1']
finished: added
'score_Cholangiocyte_scanpyUP', score of gene set (adata.obs).
450 total control genes are used. (0:00:00)
computing score 'score_TAmplifying_scanpyUP'
finished: added
'score_TAmplifying_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_EntericGlial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Slc18a2', 'Aldh1a3', 'Foxd3', 'S100b']
finished: added
'score_EntericGlial_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_Adipocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Lep', 'Fabp4', 'Tcf21', 'Adipoq', 'P2rx5', 'Ucp1', 'Cidea', 'Lhx8']
finished: added
'score_Adipocyte_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Chondrocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Col6a1', 'Cytl1', 'Lum', 'Scrg1']
finished: added
'score_Chondrocyte_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_HematoMultipotentPC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tal1']
finished: added
'score_HematoMultipotentPC_scanpyUP', score of gene set (adata.obs).
148 total control genes are used. (0:00:00)
computing score 'score_HematoStem_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Avp', 'Crhbp', 'Cd34']
finished: added
'score_HematoStem_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Basophil_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ms4a3', 'Hdc', 'Cpa3']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_CommonLymphoidPC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Dntt', 'Iglc1', 'Vpreb2']
finished: added
'score_CommonLymphoidPC_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ProBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd72', 'Irf4', 'Tcl1']
finished: added
'score_ProBcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ImmaturecDC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Axl', 'Gm15922']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Schwann_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ngfr', 'S100b']
finished: added
'score_Schwann_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_Glial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Slc18a2', 'Aldh1a3', 'Foxd3', 'S100b', 'Ngfr']
finished: added
'score_Glial_scanpyUP', score of gene set (adata.obs).
299 total control genes are used. (0:00:00)
computing score 'score_Paneth_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Nod2']
finished: added
'score_Paneth_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_InnateLymphoid_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cd7', 'Il2rb', 'Xcl1', 'Igfbp7', 'Ncr1', 'Klrd1', 'Prmt9', 'Gata3', 'Il1rl1', 'Il7r']
finished: added
'score_InnateLymphoid_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_HEVEndothelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Flt4', 'Ccl21a']
finished: added
'score_HEVEndothelial_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_VesselEndothelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Pecam1', 'Plvap', 'Cdh5']
finished: added
'score_VesselEndothelial_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_Pericyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sod3', 'Cspg4', 'Rgs5', 'Ndufa4l2', 'Cox4i2']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Myofibroblast_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Des', 'Actg2', 'Myh11']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_InflamFibroblast_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Mmp2', 'Il11', 'Rarres2', 'Nnmt']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_InflamMonocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccl3', 'Il1b', 'Camp']
finished: added
'score_InflamMonocyte_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_Neural_scanpyUP'
WARNING: genes are not in var_names and ignored: ['S100b', 'Gpm6b', 'Cryab']
finished: added
'score_Neural_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Enteroendocrine_scanpyUP'
finished: added
'score_Enteroendocrine_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_Goblet_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tff1', 'Klk1b27']
finished: added
'score_Goblet_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_Enterocyte_scanpyUP'
finished: added
'score_Enterocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_FollicularBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cxcr4', 'Bank1']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_GermCenterBcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Tcl1']
finished: added
'score_GermCenterBcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_Brush_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Azgp1']
finished: added
'score_Brush_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ImmatureEnterocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Aqp8']
finished: added
'score_ImmatureEnterocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ImmatureGoblet_scanpyUP'
finished: added
'score_ImmatureGoblet_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_EnterocytePC_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Car1']
finished: added
'score_EnterocytePC_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_EpithelialStem_scanpyUP'
finished: added
'score_EpithelialStem_scanpyUP', score of gene set (adata.obs).
249 total control genes are used. (0:00:00)
computing score 'score_IgAPlasma_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Igha', 'Igha', 'Jchain']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_IgGPlasma_scanpyUP'
WARNING: provided gene list has length 0, scores as 0
computing score 'score_IgMPlasma_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ighm', 'Tnfrsf17', 'Jchain']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_ILC1_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Il2rb', 'Xcl1', 'Igfbp7', 'Ncr1', 'Klrd1']
finished: added
'score_ILC1_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_ILC3_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Lst1', 'Prmt9']
finished: added
'score_ILC3_scanpyUP', score of gene set (adata.obs).
99 total control genes are used. (0:00:00)
computing score 'score_ActTcell_scanpyUP'
finished: added
'score_ActTcell_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_NaiTcell_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Sell', 'Lef1', 'Nell2', 'Camk4']
finished: added
'score_NaiTcell_scanpyUP', score of gene set (adata.obs).
149 total control genes are used. (0:00:00)
computing score 'score_McellGut_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ntrk2', 'Gm21983', 'Icam2', 'Tnfaip2']
finished: added
'score_McellGut_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Mast_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Cpa3', 'AW551984']
finished: added
'score_Mast_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ColorectalCancer_scanpyUP'
finished: added
'score_ColorectalCancer_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_T1Pneumocyte_scanpyUP'
finished: added
'score_T1Pneumocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_T2Pneumocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Napsa', 'Sftpd']
finished: added
'score_T2Pneumocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_Pneumocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Napsa', 'Sptb']
finished: added
'score_Pneumocyte_scanpyUP', score of gene set (adata.obs).
200 total control genes are used. (0:00:00)
computing score 'score_Club_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Scgb1a1', 'Bpifb1', 'Tmem45a', 'Scgb3a2']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_CiliatedEpithelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Foxj1', 'Ccdc78']
finished: added
'score_CiliatedEpithelial_scanpyUP', score of gene set (adata.obs).
199 total control genes are used. (0:00:00)
computing score 'score_Basal_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Krt5', 'Trp63']
WARNING: provided gene list has length 0, scores as 0
computing score 'score_Ionocyte_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Calca', 'Ascl1']
finished: added
'score_Ionocyte_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_ProlifMonocyte_scanpyUP'
finished: added
'score_ProlifMonocyte_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ILC2_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gata3', 'Il2ra', 'Il1rl1', 'Il7r']
finished: added
'score_ILC2_scanpyUP', score of gene set (adata.obs).
100 total control genes are used. (0:00:00)
computing score 'score_ProlifMyeloid_scanpyUP'
finished: added
'score_ProlifMyeloid_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ProlifcDC_scanpyUP'
finished: added
'score_ProlifcDC_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_Mesothelial_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Ccdc80', 'Upk3b', 'Pla2g2a', 'Prg4', 'Calb2']
finished: added
'score_Mesothelial_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_Platelet_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Gp1ba', 'Gp9', 'Itga2b', 'Itgb3', 'Ppbp']
finished: added
'score_Platelet_scanpyUP', score of gene set (adata.obs).
50 total control genes are used. (0:00:00)
computing score 'score_ProlifTAmplifying_scanpyUP'
finished: added
'score_ProlifTAmplifying_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ProlifEpithelialStem_scanpyUP'
finished: added
'score_ProlifEpithelialStem_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_ProlifEnterocytePC_scanpyUP'
finished: added
'score_ProlifEnterocytePC_scanpyUP', score of gene set (adata.obs).
150 total control genes are used. (0:00:00)
computing score 'score_CryptScoreParikh2019_scanpyUP'
WARNING: genes are not in var_names and ignored: ['Selenop', 'Dhrs9', 'Pkib']
finished: added
'score_CryptScoreParikh2019_scanpyUP', score of gene set (adata.obs).
348 total control genes are used. (0:00:00)
In [16]:
adata_anno_scores
Out[16]:
AnnData object with n_obs × n_vars = 10896 × 1233
obs: 'CELL', 'CONDITION', 'sample_type', 'donor', 'region', 'sample', 'percent_mito', 'n_counts', 'n_genes', 'batch', 'leiden', 'score_Bcell_scanpy', 'score_Fibroblast_scanpy', 'score_Endothelial_scanpy', 'score_Epithelial_scanpy', 'score_Granulocyte_scanpy', 'score_MelMelanoma_scanpy', 'score_MemBcell_scanpy', 'score_Myeloid_scanpy', 'score_NKcell_scanpy', 'score_NaiBcell_scanpy', 'score_Neutrophil_scanpy', 'score_Plasma_scanpy', 'score_CD4Tcell_scanpy', 'score_CD8Tcell_scanpy', 'score_Tcell_scanpy', 'score_CD8Tcell_IL7Rmax_scanpy', 'score_CD4Tcell_IL7Rmax_scanpy', 'score_RegTcell_scanpy', 'score_cDC1_scanpy', 'score_cDC2_scanpy', 'score_cDC_scanpy', 'score_NClassMonocyte_scanpy', 'score_pDC_scanpy', 'score_Hematopoietic_scanpy', 'score_Blymphocyte_scanpy', 'score_CD56dimNK_scanpy', 'score_CD56brightNK_scanpy', 'score_NaiCD4Tcell_scanpy', 'score_NaiCD8Tcell_scanpy', 'score_ProlifCD8Tcell_scanpy', 'score_ProlifCD4Tcell_scanpy', 'score_ProlifBcell_scanpy', 'score_CMCD4Tcell_scanpy', 'score_EMCD8Tcell_scanpy', 'score_EMCD4Tcell_scanpy', 'score_ClassMonocyte_scanpy', 'score_Macrophage_MARCO_scanpy', 'score_NKTcell_scanpy', 'score_gdTcell_scanpy', 'score_CytotoxCD4Tcell_scanpy', 'score_CytotoxCD8Tcell_scanpy', 'score_ExhCD8Tcell_scanpy', 'score_cDC_CCR7_scanpy', 'score_Langerhans_scanpy', 'score_Macrophage_MSR1_scanpy', 'score_Macrophage_CXCL9_scanpy', 'score_Monocyte_scanpy', 'score_ExhBcell_scanpy', 'score_Macrophage_scanpy', 'score_Hepatocyte_scanpy', 'score_Erythrocyte_scanpy', 'score_AlphaPancreatic_scanpy', 'score_BetaPancreatic_scanpy', 'score_DeltaPancreatic_scanpy', 'score_PPcell_scanpy', 'score_PancreaticDuctal_scanpy', 'score_PancreaticAcinar_scanpy', 'score_EpsilonPancreatic_scanpy', 'score_PancStellate_scanpy', 'score_Cholangiocyte_scanpy', 'score_TAmplifying_scanpy', 'score_EntericGlial_scanpy', 'score_Adipocyte_scanpy', 'score_Chondrocyte_scanpy', 'score_HematoMultipotentPC_scanpy', 'score_HematoStem_scanpy', 'score_Basophil_scanpy', 'score_CommonLymphoidPC_scanpy', 'score_ProBcell_scanpy', 'score_ImmaturecDC_scanpy', 'score_Schwann_scanpy', 'score_Glial_scanpy', 'score_Paneth_scanpy', 'score_InnateLymphoid_scanpy', 'score_HEVEndothelial_scanpy', 'score_VesselEndothelial_scanpy', 'score_Pericyte_scanpy', 'score_Myofibroblast_scanpy', 'score_InflamFibroblast_scanpy', 'score_InflamMonocyte_scanpy', 'score_Neural_scanpy', 'score_Enteroendocrine_scanpy', 'score_Goblet_scanpy', 'score_Enterocyte_scanpy', 'score_FollicularBcell_scanpy', 'score_GermCenterBcell_scanpy', 'score_Brush_scanpy', 'score_ImmatureEnterocyte_scanpy', 'score_ImmatureGoblet_scanpy', 'score_EnterocytePC_scanpy', 'score_EpithelialStem_scanpy', 'score_IgAPlasma_scanpy', 'score_IgGPlasma_scanpy', 'score_IgMPlasma_scanpy', 'score_ILC1_scanpy', 'score_ILC3_scanpy', 'score_ActTcell_scanpy', 'score_NaiTcell_scanpy', 'score_McellGut_scanpy', 'score_Mast_scanpy', 'score_ColorectalCancer_scanpy', 'score_T1Pneumocyte_scanpy', 'score_T2Pneumocyte_scanpy', 'score_Pneumocyte_scanpy', 'score_Club_scanpy', 'score_CiliatedEpithelial_scanpy', 'score_Basal_scanpy', 'score_Ionocyte_scanpy', 'score_ProlifMonocyte_scanpy', 'score_ILC2_scanpy', 'score_ProlifMyeloid_scanpy', 'score_ProlifcDC_scanpy', 'score_Mesothelial_scanpy', 'score_Platelet_scanpy', 'score_ProlifTAmplifying_scanpy', 'score_ProlifEpithelialStem_scanpy', 'score_ProlifEnterocytePC_scanpy'
var: 'ENSEMBL', 'SYMBOL', 'n_cells', 'total_counts', 'frac_reads', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std'
uns: 'hvg', 'leiden', 'leiden_colors', 'neighbors', 'pca', 'rank_genes_groups', 'region_colors', 'umap'
obsm: 'X_pca', 'X_umap', 'X_tsne'
varm: 'PCs'
obsp: 'connectivities', 'distances'
In [17]:
adata_IMM_scores
Out[17]:
AnnData object with n_obs × n_vars = 10896 × 1233
obs: 'CELL', 'CONDITION', 'sample_type', 'donor', 'region', 'sample', 'percent_mito', 'n_counts', 'n_genes', 'batch', 'leiden', 'score_HumanCD45p_scseqCMs6_ActB_scanpy', 'score_HumanCD45p_scseqCMs6_Activation_scanpy', 'score_HumanCD45p_scseqCMs6_Basophil_scanpy', 'score_HumanCD45p_scseqCMs6_Bcells_scanpy', 'score_HumanCD45p_scseqCMs6_CCG1S_scanpy', 'score_HumanCD45p_scseqCMs6_CCG2M_scanpy', 'score_HumanCD45p_scseqCMs6_Cafs_scanpy', 'score_HumanCD45p_scseqCMs6_Cellcycle_scanpy', 'score_HumanCD45p_scseqCMs6_Checkpoint_scanpy', 'score_HumanCD45p_scseqCMs6_Cyto_scanpy', 'score_HumanCD45p_scseqCMs6_Cytotox_scanpy', 'score_HumanCD45p_scseqCMs6_DCR_scanpy', 'score_HumanCD45p_scseqCMs6_DCrec_scanpy', 'score_HumanCD45p_scseqCMs6_DCs_scanpy', 'score_HumanCD45p_scseqCMs6_Eff_scanpy', 'score_HumanCD45p_scseqCMs6_Endo_scanpy', 'score_HumanCD45p_scseqCMs6_Endot_scanpy', 'score_HumanCD45p_scseqCMs6_Endothelial_scanpy', 'score_HumanCD45p_scseqCMs6_Eosinophil_scanpy', 'score_HumanCD45p_scseqCMs6_Epith_scanpy', 'score_HumanCD45p_scseqCMs6_ExhB_scanpy', 'score_HumanCD45p_scseqCMs6_Granulo_scanpy', 'score_HumanCD45p_scseqCMs6_HLA_scanpy', 'score_HumanCD45p_scseqCMs6_HLAP_scanpy', 'score_HumanCD45p_scseqCMs6_HLAS_scanpy', 'score_HumanCD45p_scseqCMs6_Ifi_scanpy', 'score_HumanCD45p_scseqCMs6_Ifng_scanpy', 'score_HumanCD45p_scseqCMs6_Macrophage_scanpy', 'score_HumanCD45p_scseqCMs6_Mast_scanpy', 'score_HumanCD45p_scseqCMs6_Megakaryocytes_scanpy', 'score_HumanCD45p_scseqCMs6_MelMelan_scanpy', 'score_HumanCD45p_scseqCMs6_MelMesen_scanpy', 'score_HumanCD45p_scseqCMs6_MemB_scanpy', 'score_HumanCD45p_scseqCMs6_Memory_scanpy', 'score_HumanCD45p_scseqCMs6_Mo14_scanpy', 'score_HumanCD45p_scseqCMs6_Mo16_scanpy', 'score_HumanCD45p_scseqCMs6_MoMa_scanpy', 'score_HumanCD45p_scseqCMs6_Monocytes_scanpy', 'score_HumanCD45p_scseqCMs6_Myelo_scanpy', 'score_HumanCD45p_scseqCMs6_MyeloSubtype_scanpy', 'score_HumanCD45p_scseqCMs6_NKT_scanpy', 'score_HumanCD45p_scseqCMs6_NKcells_scanpy', 'score_HumanCD45p_scseqCMs6_NKcyt_scanpy', 'score_HumanCD45p_scseqCMs6_NKnai_scanpy', 'score_HumanCD45p_scseqCMs6_Naive_scanpy', 'score_HumanCD45p_scseqCMs6_NaiveB_scanpy', 'score_HumanCD45p_scseqCMs6_Neutrophil_scanpy', 'score_HumanCD45p_scseqCMs6_NonEff_scanpy', 'score_HumanCD45p_scseqCMs6_OMyelo_scanpy', 'score_HumanCD45p_scseqCMs6_Others_scanpy', 'score_HumanCD45p_scseqCMs6_Plasma_scanpy', 'score_HumanCD45p_scseqCMs6_Pyro_scanpy', 'score_HumanCD45p_scseqCMs6_Stemmess_scanpy', 'score_HumanCD45p_scseqCMs6_StemmessS_scanpy', 'score_HumanCD45p_scseqCMs6_Stromal_scanpy', 'score_HumanCD45p_scseqCMs6_T4CM_scanpy', 'score_HumanCD45p_scseqCMs6_TAM_scanpy', 'score_HumanCD45p_scseqCMs6_TAMCx_scanpy', 'score_HumanCD45p_scseqCMs6_TEM_scanpy', 'score_HumanCD45p_scseqCMs6_TMO_scanpy', 'score_HumanCD45p_scseqCMs6_TMid_scanpy', 'score_HumanCD45p_scseqCMs6_TNK_scanpy', 'score_HumanCD45p_scseqCMs6_TStem_scanpy', 'score_HumanCD45p_scseqCMs6_TStemhi_scanpy', 'score_HumanCD45p_scseqCMs6_TSteml_scanpy', 'score_HumanCD45p_scseqCMs6_TStemlo_scanpy', 'score_HumanCD45p_scseqCMs6_TTh1_scanpy', 'score_HumanCD45p_scseqCMs6_TTh17_scanpy', 'score_HumanCD45p_scseqCMs6_TTh2_scanpy', 'score_HumanCD45p_scseqCMs6_Tcd4_scanpy', 'score_HumanCD45p_scseqCMs6_Tcd8_scanpy', 'score_HumanCD45p_scseqCMs6_Tcells_scanpy', 'score_HumanCD45p_scseqCMs6_Tcgd_scanpy', 'score_HumanCD45p_scseqCMs6_Tcytox_scanpy', 'score_HumanCD45p_scseqCMs6_Teff_scanpy', 'score_HumanCD45p_scseqCMs6_Tfh_scanpy', 'score_HumanCD45p_scseqCMs6_TilCM_scanpy', 'score_HumanCD45p_scseqCMs6_Tpexh_scanpy', 'score_HumanCD45p_scseqCMs6_Treg_scanpy', 'score_HumanCD45p_scseqCMs6_Ttexh_scanpy', 'score_HumanCD45p_scseqCMs6_Ubi_scanpy', 'score_HumanCD45p_scseqCMs6_UnivExh_scanpy', 'score_HumanCD45p_scseqCMs6_UnivMem_scanpy', 'score_HumanCD45p_scseqCMs6_UnivNaive_scanpy', 'score_HumanCD45p_scseqCMs6_aDCs_scanpy', 'score_HumanCD45p_scseqCMs6_allSteml_scanpy', 'score_HumanCD45p_scseqCMs6_cDC1_scanpy', 'score_HumanCD45p_scseqCMs6_cDC2_scanpy', 'score_HumanCD45p_scseqCMs6_cDCs_scanpy', 'score_HumanCD45p_scseqCMs6_epDCs_scanpy', 'score_HumanCD45p_scseqCMs6_general_scanpy', 'score_HumanCD45p_scseqCMs6_moDC_scanpy', 'score_HumanCD45p_scseqCMs6_pDCs_scanpy', 'score_HumanCD45p_scseqCMs6_uDCs_scanpy'
var: 'ENSEMBL', 'SYMBOL', 'n_cells', 'total_counts', 'frac_reads', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std'
uns: 'hvg', 'leiden', 'leiden_colors', 'neighbors', 'pca', 'rank_genes_groups', 'region_colors', 'umap'
obsm: 'X_pca', 'X_umap', 'X_tsne'
varm: 'PCs'
obsp: 'connectivities', 'distances'
In [18]:
adata_crypt_scores
Out[18]:
AnnData object with n_obs × n_vars = 10896 × 1233
obs: 'CELL', 'CONDITION', 'sample_type', 'donor', 'region', 'sample', 'percent_mito', 'n_counts', 'n_genes', 'batch', 'leiden', 'score_CryptScoreParikh2019_scanpy'
var: 'ENSEMBL', 'SYMBOL', 'n_cells', 'total_counts', 'frac_reads', 'highly_variable', 'means', 'dispersions', 'dispersions_norm', 'mean', 'std'
uns: 'hvg', 'leiden', 'leiden_colors', 'neighbors', 'pca', 'rank_genes_groups', 'region_colors', 'umap'
obsm: 'X_pca', 'X_umap', 'X_tsne'
varm: 'PCs'
obsp: 'connectivities', 'distances'
In [19]:
sc.pl.umap(adata_IMM_scores, color=['score_HumanCD45p_scseqCMs6_Cellcycle_scanpy',
'score_HumanCD45p_scseqCMs6_CCG1S_scanpy',
'score_HumanCD45p_scseqCMs6_CCG2M_scanpy',
'score_HumanCD45p_scseqCMs6_Stemmess_scanpy',
], legend_loc='on data',legend_fontsize=6)
In [20]:
sc.pl.umap(adata_anno_scores, color=['score_Epithelial_scanpy',
'score_Fibroblast_scanpy',
'score_Endothelial_scanpy',
'score_Hematopoietic_scanpy',
], legend_loc='on data',legend_fontsize=6)
In [21]:
sc.pl.umap(adata_anno_scores, color=['score_Paneth_scanpy',
'score_Brush_scanpy', # Tuft cells
'score_Enteroendocrine_scanpy' # EEC
], legend_loc='on data',legend_fontsize=6)
In [22]:
sc.pl.umap(adata_anno_scores, color=['score_EpithelialStem_scanpy',
'score_TAmplifying_scanpy',
'score_ImmatureGoblet_scanpy',
'score_Goblet_scanpy',
], legend_loc='on data',legend_fontsize=6)
In [23]:
sc.pl.umap(adata_anno_scores, color=['score_EpithelialStem_scanpy',
'score_EnterocytePC_scanpy', # Enterocyte progenitor cell
'score_ImmatureEnterocyte_scanpy',
'score_Enterocyte_scanpy'], legend_loc='on data',legend_fontsize=6)
In [24]:
sc.pl.umap(adata_anno_scores, color=['score_TAmplifying_scanpy',
'score_ProlifTAmplifying_scanpy',
], legend_loc='on data',legend_fontsize=6)
In [25]:
sc.pl.umap(adata_crypt_scores, color=['score_CryptScoreParikh2019_scanpy'], legend_loc='on data',legend_fontsize=6)
In [26]:
sc.pl.umap(adata,color=['Alpi','Apoa1','Apoa4','Fabp1']) ## enterocyte
In [27]:
sc.pl.umap(adata,color=['Muc2','Tff3','Agr2']) ## goblet
In [28]:
sc.pl.umap(adata,color=['Chga','Chgb','Tac1','Neurog3','Tph1']) ## enteroendocrine
In [29]:
sc.pl.umap(adata,color=['Ascl2','Slc12a2','Axin2','Olfm4','Gkn3','Lgr5']) ## progenitor
In [30]:
sc.pl.umap(adata,color=['Dclk1','Trpm5','Gfi1b','Il25']) ## Tuft/Brush
In [31]:
sc.pl.umap(adata,color=['Epcam','Krt18','Krt19']) ## Epithelial
Generate UMAPs for all signatures¶
In [32]:
scores = [x for x in adata_anno_scores.obs.columns if 'scanpy' in x]
sc.pl.umap(adata_anno_scores, color=scores, color_map='viridis')
